Zafar249/Gender_Classification

1import gradio as gr2import numpy as np3import joblib4import json5import pandas as pd6 7disclaimer = """8**Disclaimer:** This is a demo/prototype for educational/experimental purposes only. 9Do not rely on this for real-world decisions. The creator is not responsible for any misuse or consequences.10"""11 12def predict_gender(color, genre, beverage, drink):13    # Predicts the gender of a person using the input features 14 15    # Open file in read binary format16    file = open("model.joblib", "rb")17 18    # Load the model19    model = joblib.load(file)20 21    file2 = open("columns.json")22 23    # Load a list of columns used in the training of the model24    training_columns = json.load(file2)25 26    # Create a dataframe using the input features passed as arguments27    test_df = pd.DataFrame([{28        "Favorite Color": color,29        "Favorite Music Genre": genre,30        "Favorite Beverage": beverage,31        "Favorite Soft Drink": drink32    }])33 34    for col in test_df.columns:35        # One-hot encode the categorical variables and convert them to labels36        dummy = pd.get_dummies(test_df[col])37 38        # Concatenate the dummy column with the dataframe39        test_df = pd.concat([test_df, dummy], axis=1)40 41        # Drop the irrelevant column42        test_df.drop(col, axis=1, inplace=True)43 44    # Reshape the dataframe so that it can be inputted into the model45    test_df = test_df.reindex(columns=training_columns, fill_value=0)46 47    # Get a prediction of the gender using the input features and the model48    y_pred = model.predict(test_df)[0]49 50    # If the model predicts gender to be male51    if y_pred:52        y_pred = "Male"53    # Else the gender is female54    else:55        y_pred = "Female"56 57    return y_pred58 59 60# Define a list of inputs61inputs = [62    gr.Radio(63        choices=["Cool", "Neutral", "Warm"],64        label = "Favourite Color?",65        interactive=True66    ),67    gr.Dropdown(68        choices=sorted(["Electronic", "Folk/Traditional", "Pop", "R&B and soul", "Rock", "Hip hop", "Jazz/Blues"]),69        label="Favourite Music?",70        interactive=True71    ),72    gr.Dropdown(73        choices=sorted(["Vodka", "Beer", "Wine", "Whiskey"]) + ["Other", "Doesn't drink"],74        label="Favourite Beverage?",75        interactive=True76    ),77    gr.Radio(78        choices=["Coca Cola/Pepsi", "7UP/Sprite", "Fanta", "Other"],79        label = "Favourite Soft Drink?",80        interactive=True81    )82]83 84# Create a gradio interface85demo = gr.Interface(86    fn = predict_gender,  # functio to use87    inputs = inputs,88    outputs = ["text"],89    description=disclaimer90)91 92# Launch the interface93demo.launch()